|Intitulé||Numerical Algebraic Geometry and Algebraic Numerical Analysis|
|Organisateurs||Michele Bolognesi et Daniele A. Di Pietro|
|Objectifs||Ce groupe de travail a pour but d'explorer des développements récents au carrefour entre la géométrie algébrique et l'analyse numérique. Au passage, il permettra de renforcer les liens entre les équipes de mathématiques fondamentales et appliquées de l'IMAG.|
|Structure||Deux-trois séances par an animées par des orateurs internationaux de très haut niveau|
ANR projects HHOMM and fast4hho
Introduction and applications of Numerical Algebraic Geometry
Part I: Introduction to Numerical Algebraic Geometry. Nonlinear polynomial equations have been solved for several millennia such as those documented on Babylonian clay tablets involving the relationship between perimeter and area of rectangles. The Abel-Ruffini theorem and the development of Galois theory two centuries ago showed that solutions to most systems of polynomial equations could not be expressed in terms of radicals necessitating development of numerical computational methods to approximate solutions. This talk will explore various numerical methods for computing and analyzing solutions to systems of polynomial equations, collectively called numerical algebraic geometry. Some recent results for polynomial systems arising in science and engineering applications along with current computational challenges associated with solving polynomial systems will be discussed.
Part II: Applications of Numerical Algebraic Geometry. Systems of nonlinear polynomial equations arise in a variety of fields in mathematics, science, and engineering. Many numerical techniques for solving and analyzing solution sets of polynomial equations over the complex numbers, collectively called numerical algebraic geometry, have been developed over the past several decades. However, since real solutions are the only solutions of interest in many applications, there is a current emphasis on developing new methods for computing and analyzing real solution sets. This talk will summarize some numerical real algebraic geometric approaches as well as recent successes of these methods for solving a variety of problems in science and engineering.
High order Whitney forms on simplices
Whitney elements on simplices are perhaps the most widely used finite elements in computational electromagnetics. They offer the simplest construction of polynomial iscrete differential forms on simplicial complexes. Their associated degrees of freedom (dofs) have a very clear physical meaning and give a recipe for discretizing physical balance laws, e.g., Maxwell's equations. As interest grew for the use of high order schemes, such as hp-finite element or spectral element methods, higher-order extensions of Whitney forms have become an important computational tool, appreciated for their better convergence and accuracy properties. However, it has remained unclear what kind of cochains such elements should be associated with: Can the corresponding dofs be assigned to precise geometrical elements of the mesh, just as, for instance, a degree of freedom for the space of Whitney 1-forms belongs to a specific edge? We address this localization issue. Why is this an issue? The existing constructions of high order extensions of Whitney elements follow the traditional FEM path of using higher and higher "moments" to define the needed dofs. As a result, such high order finite $k$-elements in $n$ dimensions include dofs associated to $q$-simplices, with $k < q \le n$ , whose physical interpretation is obscure. The present presentation offers an approach based on the so-called "small simplices", a set of subsimplices obtained by homothetic contractions of the original mesh simplices, centered at mesh nodes (or more generally, when going up in degree, at points of the principal lattice of each original simplex). Degrees of freedom of the high-order Whitney k-forms are then associated with small simplices of dimension k only. We provide an explicit basis for these elements on simplices and we justify this approachfrom a geometric point of view (in the spirit of Hassler Whitney's approach, still successful 30 years after his death).
Spline functions for geometric modeling and numerical simulation
In geometric modeling, a standard representation of shapes is based on parameterized surfaces or volumes, which involve piecewise polynomial functions also known as splines. We will first describe these splines, in the univariate case, how they are characterized and what are their main properties. We will present some extensions to higher dimensions and how they are used for modeling shapes, in several domains of applications. We will also illustrate several exemples of spline constructions, that have been investigated. In the last decades, a new paradigm called isogeometric analysis has emerged, which uses splines functions not only to describe the geometry but also to approximate functions on this geometry. We will briefly describe how this approach is working in numerical simulation, what are its main characteristics and we will provide some illustrations. Analyzing the spaces of spline functions associated to a given domain partition or a given abstract topology is an important problem for geometric modeling and numerical simulations. We will present some of the know results and some problems still open. We will describe algebraic-geometric techniques, which provide a better insight on these spline spaces, in particular for the analysis of their dimension and for the construction of basis. This analysis involves topological complexes and homological tools, which will be explained by examples. Spline spaces over triangular meshes or T-meshes, in dimension 2 and 3, as well as extensions to geometrically smooth spline spaces (if time permits) will be considered in details.
From the finite element method to the finite element exterior calculus
The finite element exterior calculus (FEEC) has been developed in the early 2000s as a mathematical framework that uses the calculus of differential forms for the formulation of the finite element method. The aim of this lecture is to revisit some of the main aspects of FEEC. We shall use as a main motivation the approximation of Laplace equation in mixed form and of the time harmonic formulation of Maxwell's equations. It is remarkable that, besides providing a more elegant and comprehensive understanding of the existing theory, the FEEC allows for the development of new finite elements and for the solution of problems that would be difficult, if not impossible, to address with more traditional tools